# Where Does AI Leave a Footprint? Children's Reasoning About AI's Environmental Costs

arXiv: https://arxiv.org/abs/2603.27376 · HTML: https://mlsanity.com/paper/2603.27376/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 10 of its 117 references that are in the map.
- First posted on arXiv 28 Mar 2026.

## Builds on (most cited first, 10 of 10)

- [Carbon Emissions and Large Neural Network Training](https://mlsanity.com/paper/2104.10350/) (2021)
- [The rising costs of training frontier AI models](https://mlsanity.com/paper/2405.21015/) (2024)
- [How Hungry is AI? Benchmarking Energy, Water, and Carbon Footprint of LLM Inference](https://mlsanity.com/paper/2505.09598/) (2025)
- [Unraveling the Hidden Environmental Impacts of AI Solutions for Environment](https://mlsanity.com/paper/2110.11822/) (2021)
- [Constructing Dreams using Generative AI](https://mlsanity.com/paper/2305.12013/) (2023)
- [Data Feminism for AI](https://mlsanity.com/paper/2405.01286/) (2024)
- [Children's Mental Models of AI Reasoning: Implications for AI Literacy Education](https://mlsanity.com/paper/2505.16031/) (2025)
- [Representation Bias of Adolescents in AI: A Bilingual, Bicultural Study](https://mlsanity.com/paper/2408.01961/) (2024)
- ["AI just keeps guessing": Using ARC Puzzles to Help Children Identify Reasoning Errors in Generative AI](https://mlsanity.com/paper/2505.16034/) (2025)
- ["If anybody finds out you are in BIG TROUBLE": Understanding Children's Hopes, Fears, and Evaluations of Generative AI](https://mlsanity.com/paper/2505.16089/) (2025)

## Abstract (arXiv)

Two of the most socially consequential issues facing today's children are the rise of artificial intelligence (AI) and the rapid changes to the earth's climate. Both issues are complex and contested, and they are linked through the notable environmental costs of AI use. Using a systems thinking framework, we developed an interactive system called Ecoprompt to help children reason about the environmental impact of AI. EcoPrompt combines a prompt-level environmental footprint calculator with a simulation game that challenges players to reason about the impact of AI use on natural resources that the player manages. We evaluated the system through two participatory design sessions with 16 children ages 6-12. Our findings surfaced children's perspectives on societal and environmental tradeoffs of AI use, as well as their sense of agency and responsibility. Taken together, these findings suggest opportunities for broadening AI literacy to include systems-level reasoning about AI's environmental impact.